The Geometry of Ecological Interactions Simplifying Spatial Complexity [Paperback]

Provides introduction to exciting new areas of spatial ecological theory, simplifying spatial complexity.The field of theoretical ecology has expanded dramatically in the last few years. Some of the most interesting work has been done using spatial models with stochasticity. This book brings together the best researchers working with this type of model to look at its role in the investigation of ecosystem dynamics. The book will be of broad interest to theoretical ecologists as it contains not only mathematically rigorous treatments, but also their application to real ecological problems, and suggests ways of extending and evaluating such modelling techniques in the future.The field of theoretical ecology has expanded dramatically in the last few years. Some of the most interesting work has been done using spatial models with stochasticity. This book brings together the best researchers working with this type of model to look at its role in the investigation of ecosystem dynamics. The book will be of broad interest to theoretical ecologists as it contains not only mathematically rigorous treatments, but also their application to real ecological problems, and suggests ways of extending and evaluating such modelling techniques in the future.The field of theoretical ecology has expanded dramatically in the past few years, while some of the most interesting work has been done using spatial models with stochasticity. This timely volume brings together the work of leading researchers working with this model and explores its role in the study of ecosystem dynamics. With its mathematically rigorous treatments, applications to real ecological problems, and proposals for extending the use of such modeling techniques in the future, this resource will be of great interest to all researchers in theoretical ecology, mathematical biology, and ecosystems analysis.1. Introduction Richard Law, Ulf Dieckmann and J. A. J. Metz; Part I. Empirical and Statistical Background: 2. A neighbol.